Tag Archives: transcriptome

Transcriptomes in space. Sweet.

I know a lot of sci-geeks were lured into the field by space. Rockets, space travel, great science fiction–I understand the appeal. But as it seemed much more physics oriented, space wasn’t my primary fascination. But the effects of space travel on organisms (humans, of course, but others as well)–that’s something I can find pretty intriguing. And I was always really pleased to hear about the various cells and organisms that were on the trips and undergoing experimentation.

But until last week, had never gone to the primary literature that resulted from these studies to have a look. I had seen an article in Wired that talked about the work, though, and I had to see it. Have a look at the piece How Plants Deal With Space Travel for their take on it. Coincidentally on Fascination of Plants Day a piece appeared in SciAm as well, on other Plants! In! Space! (Moon trees were totally new to me in that piece, but I was previously familiar with Space Beer barley.)

What does happen to gene expression in space? It changes in some expected ways: the structural features of the cytoskeleton can be affected, as can metabolism. These had been previously described. But with new technologies now they can look more broadly across the genome to see further details.

This is not your average experiment, though. One set needs to be run on the ground as a control, while the other one needs to be loaded on to spacecraft, monitored for all sorts of external conditions, and run in the shuttle. They spent a bit of time explaining how they coordinated those to be sure they were making as direct comparisons as possible. But they get all that under control, and have a look at the Arabidopsis plants in a couple of ways.

They have seedlings to look at, but they also used tissue culture cells. I think that’s an interesting thing to do–it gets at some of the differences between structural features that might be more affected by gravity in an intact plant vs. a dish. And you can also think about the differences in tissue types.

The space seedlings had a lot of upregulation of pathogen/wound response genes. Other stress-response genes were up as well. Downregulated genes were curious to me: a lot of transcription factors went down, but cell wall metabolism and elongation ones did too. I might have expected the cell walls to have to try harder if the cytoskeleton was misbehaving. Gravitropism genes were down, which seems sensible.

The cultured cells were different. They ramped up their heat shock genes more, but also did have some stress-responses for wounding and other conditions too. But of course, all of the scenarios included lots of things that would have to be characterized in more detail to fully understand.  The general features are interesting and informative, but some specific genes might provide interesting clues too.

One of the things that struck me was that the tissue cultures cells could be more prepared to just throw some “on” switches because they are more undifferentiated–or at least not under the same tissue-specific constraints that seedlings are. That could explain some of the transcription factor differences. And they go into that a bit in the discussion.

They go into more details and offer lists of the genes to examine, and in the discussion they speculate about some of the differences between the conditions. But I imagine it’s important to examine both scenarios. If I was on a long space flight I’d want some fresh veggies to eat, but maybe also some cultured cells in a vat to produce various things–including oxygen.

I don’t imagine this information is anything I need to know soon–I have no plans for flight myself, although I think recently Trey bought a lottery ticket for that… I’m glad someone is looking at it.

When I contacted the team with a question about the paper, Anna-Lisa Paul also pointed me to this video. You can see her trying to work on a sample project like it would happen in space. Funny, just the other day I posted about that guy who needed to get genome samples from dangerous critters–now there’s this. Genomics can be a lot more physically challenging than you might think–it’s not all done on keyboards!


Paul, A., Zupanska, A., Ostrow, D., Zhang, Y., Sun, Y., Li, J., Shanker, S., Farmerie, W., Amalfitano, C., & Ferl, R. (2012). Spaceflight Transcriptomes: Unique Responses to a Novel Environment Astrobiology, 12 (1), 40-56 DOI: 10.1089/ast.2011.0696

Video Tips of the Week: Annual Review IV, 2nd half

As you may know, we’ve been doing these video tips-of-the-week for FOUR years now. We have completed around 200 little tidbit introductions to various resources from last year, 2011 (yep, it’s 2012 now). At the end of the year we’ve established a sort of holiday tradition: we are doing a summary post to collect them all. If you have missed any of them it’s a great way to have a quick look at what might be useful to your work.

You can see past years’ tips here: 2008 I2008 II2009 I2009 II2010 I2010 II. The summary of the first half of 2011 is available from last week.

July 2011

July 6: Prioritizing genes using the Gene Prioritization Portal

July 13: PolySearch, searching many databases at once

July 20: Human Epigenomics Visualization Hub

July 27: The new SIB Bioinformatics Resource Portal


August 2011

August 3: SNPexp, correlation between SNPs and gene expression 

August 10: CompaGB for comparing genome browser software

August 17: CoGe, comparing genomes revisited

August 24: Domain Draw for quick motif diagrams

August 31: From UniProt to the PSI SBKB and back again


September 2011

September 7: Plant comparative genomics using Plaza

September 14: phiGENOME for bacteriophage genome exploration

September 21: Getting flanking sequences of genomic locations

September 28: Introduction to R statistical software 


October 2011

October 5: VnD resource for genetic variation and drug information

October 12: Track Hubs in UCSC Genome Browser

October 19: Mitochondrial Transcriptome GBrowser 

October 26: Variation data from Ensembl


November 2011

November 2: MizBee Synteny Browser

November 9: The new database of genomic variants: DGV2

November 16: MapMi, automated mapping of microRNA loci

November 23: BioMart’s new central portal

November 30: Phosphida, a post-translational modification database

December 2011

December 7: VarSifter, for identifying key sequence variations

December 14: Big changes to NCBI’s genome resources

December 21: eggNOG for the Holidays (or to explore orthologous genes)

December 28: Video Tips of the Week: Annual Review IV (first half of 2011)